The average data center infrastructure is designed to handle an average load and is sometimes over-provisioned with computational and storage resources to handle some sort of peak load. However, when a new project comes in, the new project often requires upgrading the current infrastructure or adding additional infrastructure. Setting up new servers or upgrading old servers may take a significant amount of time. Additionally, migrating workloads to the additional infrastructure results in significant downtime.
Having the ability to migrate some workloads to one or more public “cloud” servers provides a cost-efficient solution that avoids setting up new servers or upgrading old servers. However, the migration process still typically requires extensive up-front planning and significant downtime, especially in cases where there is a large amount of data to transfer.
Traditional workload migration includes a process of copying over data stored on-premises to cloud servers while simultaneously running a workload on-premises. Once the data is fully copied to the cloud servers, the data is synchronized and the workload execution context is transitioned to the cloud. Significant downtime is accrued and workload disruption is at its peak when performing data synchronization tasks and transitioning the workload execution context to the cloud. Additionally, using this traditional approach, the workload cannot be executed on the cloud until the entire migration is complete.
U.S. Pat. No. 9,753,669, titled “Real Time Cloud Bursting”, and referred to herein as the “Cloud Bursting application” presents a solution that starts the migration process on-demand by decoupling the computing processes and the storage resources that a server is using to execute a workload and transferring the computing process to the cloud. Transferring the computing processes to the cloud immediately grants benefits of having additional computing resource while making valuable data center resources available for re-allocation.
Once one or more workloads are executing in the cloud, workload data residing in the data center may still need to be migrated to the cloud. Unfortunately, migrating the workload data from the data center to the cloud normally requires stopping the computing processes that are using the workload data to prevent the workload data from being modified during the migration process. Additionally, workload data copied from the data center to the cloud may remain unused for a significant amount of time before benefits of having that workload data available on the cloud may be realized.
The approaches described in this section are approaches that could be pursued, but not necessarily approaches that have been previously conceived or pursued. Therefore, unless otherwise indicated, it should not be assumed that any of the approaches described in this section qualify as prior art merely by virtue of their inclusion in this section.